Semidefinite Hankel-type Model Reduction Based on Frequency Response Matching
(2013) In IEEE Transactions on Automatic Control- Abstract
- This paper is dedicated to model order reduction of linear time-invariant systems. The main contribution of this paper is the derivation of two scalable stability-preserving model reduction algorithms. Both algorithms constitute a development of a recently proposed model reduction method. The algorithms perform a curve fitting procedure using frequency response samples of a model and semidefinite programming methods. Computation of these samples can be done efficiently even for large scale models. Both algorithms are obtained from a reformulation of the model reduction problem. One proposes a semidefinite relaxation, while the other is an iterative semidefinite approach. The relaxation approach is similar to Hankel model reduction, which... (More)
- This paper is dedicated to model order reduction of linear time-invariant systems. The main contribution of this paper is the derivation of two scalable stability-preserving model reduction algorithms. Both algorithms constitute a development of a recently proposed model reduction method. The algorithms perform a curve fitting procedure using frequency response samples of a model and semidefinite programming methods. Computation of these samples can be done efficiently even for large scale models. Both algorithms are obtained from a reformulation of the model reduction problem. One proposes a semidefinite relaxation, while the other is an iterative semidefinite approach. The relaxation approach is similar to Hankel model reduction, which is a well-known and established method in the control literature. Due to this resemblance, the accuracy of approximation is also similar to the one of Hankel model reduction. An appealing quality of the proposed algorithms is the ability to easily perform extensions, e.g., introduce frequency-weighting, positive-real and bounded-real constraints. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2544108
- author
- Sootla, Aivar LU
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Reduced order modeling, Model/controller reduction, Optimization, Semidefinite programming
- in
- IEEE Transactions on Automatic Control
- article number
- 6298942
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:84875609679
- ISSN
- 0018-9286
- project
- LCCC
- language
- English
- LU publication?
- no
- additional info
- Preprint accepted for publication
- id
- 55e04a9b-d4f8-4100-964e-7599203784fa (old id 2544108)
- date added to LUP
- 2016-04-04 13:32:38
- date last changed
- 2022-02-28 22:32:24
@article{55e04a9b-d4f8-4100-964e-7599203784fa,
abstract = {{This paper is dedicated to model order reduction of linear time-invariant systems. The main contribution of this paper is the derivation of two scalable stability-preserving model reduction algorithms. Both algorithms constitute a development of a recently proposed model reduction method. The algorithms perform a curve fitting procedure using frequency response samples of a model and semidefinite programming methods. Computation of these samples can be done efficiently even for large scale models. Both algorithms are obtained from a reformulation of the model reduction problem. One proposes a semidefinite relaxation, while the other is an iterative semidefinite approach. The relaxation approach is similar to Hankel model reduction, which is a well-known and established method in the control literature. Due to this resemblance, the accuracy of approximation is also similar to the one of Hankel model reduction. An appealing quality of the proposed algorithms is the ability to easily perform extensions, e.g., introduce frequency-weighting, positive-real and bounded-real constraints.}},
author = {{Sootla, Aivar}},
issn = {{0018-9286}},
keywords = {{Reduced order modeling; Model/controller reduction; Optimization; Semidefinite programming}},
language = {{eng}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Automatic Control}},
title = {{Semidefinite Hankel-type Model Reduction Based on Frequency Response Matching}},
url = {{https://lup.lub.lu.se/search/files/6145911/2544110.pdf}},
year = {{2013}},
}